Triple
T12021025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia 3310 (2017) |
E286147
|
entity |
| Predicate | displayColorSupport |
P102580
|
FINISHED |
| Object | color |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: color | Statement: [Nokia 3310 (2017), displayColorSupport, color]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: displayColorSupport Context triple: [Nokia 3310 (2017), displayColorSupport, color]
-
A.
hasColorDisplay
chosen
Indicates that an entity is equipped with a display capable of showing colors rather than only monochrome output.
-
B.
colorDisplay
Indicates that one entity presents, shows, or renders the color associated with another entity.
-
C.
hasColorInfo
Indicates that an entity is associated with specific color-related information or attributes.
-
D.
isColor
Indicates that one entity represents the color attribute or hue of another entity.
-
E.
colorSystemCompatibleWith
Indicates that one color system can be accurately used, interpreted, or converted within the context of another color system without loss of intended color meaning.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902b6ebbc8190b13c44a61c6f81b9 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.